Energy-efficient adaptive data compression in wireless sensor networks

Jonathan Gana Kolo*, Li Minn Ang, Kah Phooi Seng, S. Anandan Shanmugam, David Wee Gin Lim

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In wireless sensor networks (WSNs), a large number of tiny, inexpensive and computable sensor nodes are usually deployed randomly to monitor one or more physical phenomena. The sensor nodes collect and process the sensed data and send the data to the sink wirelessly. Energy consumption is however a serious problem affecting WSNs lifetime. Radio communication is often the major cause of energy consumption in wireless sensor nodes. Thus, applying data compression before transmission can significantly help in reducing the total power consumption of a sensor node. In this paper, we propose an efficient and robust adaptive data compression scheme (ADCS). The proposed scheme independently compresses each block of source data losslessly or lossily on local nodes based on the given application. Simulation results show the merits of the proposed compression scheme in comparison with other recently proposed compression algorithms for WSNs including S-LZW, LEC, MPDC, Two-modal GPC and LTC.

Original languageEnglish
Pages (from-to)229-247
Number of pages19
JournalInternational Journal of Sensor Networks
Issue number4
Publication statusPublished - 2016
Externally publishedYes


  • AEE
  • Adaptive entropy encoder
  • Data compression
  • Energy efficiency
  • Huffman coding
  • Signal processing
  • WSNs
  • Wireless sensor networks

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